Gabor Cselle

Sr PM Dir, GenAI @Google Workspace. Previously: @OpenAI, @Google, @Twitter, 3x startup founder with varied success. Better half: @ericakochi

[Gabor Cselle @gabor]

@charlieholtz @jacksondecampos @ilyasu Ilya is always a good intro!

[Gabor Cselle @gabor]

I just got a literal check in the mail for my angel investment in Conductor (acquired by Meta).

The snail mail paper check makes it a lot more real.

Thank you @charlieholtz @jacksondecampos and team and excited to see what you build next!

[Gabor Cselle @gabor]

I will miss their investor emails with the charts going 📈📈📈

[Gabor Cselle @gabor]

My wife @ericakochi’s Japan made men’s shirts are selling - shipping boxes are stacking up on their way to UPS.

What’s selling is her “Nami” shirt which shows a blue wave. The original context was the Hokusai print, but the context is a bit different now.

[Gabor Cselle @gabor]

@LyalinDotCom Is this pretraining or posttraining?

[Gabor Cselle @gabor]

What AI means for the field of mathematics - incredible article in this week’s New Yorker featuring @terrence_tao
https://t.co/2xyd8DAH2P

[Gabor Cselle @gabor]

"When you can build anything, building something great actually is now where most of the value is."

[Lenny Rachitsky @lennysan]

My biggest takeaways from Head of Product for @Gemini and Google's other frontier AI models—Tulsee Doshi (@tulseedoshi):

1. Great PMs are more in demand than ever. “When you can build anything, building something great actually is now where most of the value is,” Tulsee said. The scarce skill is now identifying which of the thousands of possible things to build is the one worth building. Alongside that is putting that judgment into practice: aligning people and converting speed-induced chaos into a coherent direction.

2. The PM role has shifted from writing requirements to creating something with “heft.” The PM who hands a requirements doc to an engineer and calls it done is not going to do well in this new environment. The new baseline is going one step further: actually producing something of substance, be it a prototype, a thorough data analysis, or even a ready-to-ship MVP.

3. Tulsee hires PMs who have opinions about models. She wants PMs who play with models every day, have their own use cases for judging whether a model is good, and stress-test capabilities themselves. They’re also technical enough to roll up their sleeves, dig into data, and build an eval. And they’re adaptive: “The space is changing every two weeks. A roadmap you wrote two months ago, you’re gonna be looking at it again and rewriting it.”

4. To understand a new model, test it on work you care about. When a new model comes out, some people try 3D animations, others creative writing or hard financial analysis. Tulsee’s advice for evaluating new models is to pick tasks where models “are already showing signs of life” but aren’t perfect by your own definition. That leaves room to see different models handle the problem differently, and it’s where you’ll notice how the models improve.

5. Model development is less like engineering and more like alchemy. “Model training is kind of like Snape’s potions class,” she says. “You can put all the ingredients in and be thoughtful about what you expect, but you also have to expect that there will be a little bit of magic.” Her team’s job is to identify where the model shines (often in ways no one planned) and to turn that into something great for users.

6. Tulsee’s 60-20-20 rule is a practical way to build ahead of the models. Your AI product roadmap should look like this: roughly 60% of what you build should work today, another 20% should be close—“not perfect, but you can see how the models might get here in the very near future”—and the final 20% should show glimmers of something magical that the model can’t quite do yet. The exact numbers are flexible, but the idea is to be ready to double down on something that just became possible.

7. Your first eval can be five prompts. When tackling evals, the most common mistake people make is waiting until you can build something large-scale before even starting. “Start with even just five prompts,” she says. “Start simple. Start with even just yourself as the rater.” A set of even 20 prompts that creates a signal between model A and model B is “so powerful.” Getting to a small, honest set of examples forces you to articulate what “good” looks like. Get clear on a set of good examples first, then scale up.

8. Burnout comes from chaos and grunt work more than from long hours. Tulsee admits everyone on her team is “putting in all of the hours.” But in her experience, burnout comes from churn and chaos, and work that feels like a waste of time. Work you’re excited about is exhausting but brings more joy. That’s why she hopes AI tools can reduce burnout by removing the grunt work, so people spend more time thinking and being creative. My tech workforce survey found the same thing: more hours doesn’t necessarily equal burnout.

9. Google’s full-stack AI strategy gives it an advantage few competitors can match. From custom TPU hardware to products used by over a billion people each, Google operates across the entire value chain. Tulsee describes Google’s goal as building models across the “Pareto curve of cost to quality”—not just the frontier LLM but models that serve a search user, a software engineer, and a cyber defender. Frontier competition matters to Google, and Tulsee is direct about Google’s intention to win the SOTA model race.

[Gabor Cselle @gabor]

@jeffseibert @elonmusk Will they come by your house to fix it?

[Gabor Cselle @gabor]

Weekends are for optimizing your agents

[Gabor Cselle @gabor]

Sunday AI run club with @richardprice100 - today’s topic: it’s easier than ever to find 10% product improvements in your code base. Why does it still take so long to get them into production?

[Gabor Cselle @gabor]

Fun seeing everyone and retell stories of shenanigans 20 years past.Thank you @brezina for organizing!

[Paul Graham @paulg]

20 years ago there was a building in SF that was nicknamed the Y Scraper because so many YC founders lived there. They just had a reunion and it makes me so happy to see them all. One thing you can say for sure about YC: no investor's founders become closer friends.

[Gabor Cselle @gabor]

@joshk sorry for misattributing it, but I got the firm right 🙈

[Gabor Cselle @gabor]

I think about this quote a lot.

[Lenny Rachitsky @lennysan]

.@illscience: "Moats are discovered, not designed."

[Gabor Cselle @gabor]

Caught up with @jamescham today and we talked about:
1/ all the builders who have been building their personal AI brain for the last 6 months
2/ how college kids can win hackathons by simply not knowing what’s supposed to be not possible

[Gabor Cselle @gabor]

@franktisellano YOU GET ME

Also tysm for coming to my XFN meeting today

[Gabor Cselle @gabor]

Feeling very AI accelerated over the past 2 weeks

[Gabor Cselle @gabor]

@RustyOnLife Nope all good

[Gabor Cselle @gabor]

@garrytan it's the RL, just WAI

[Gabor Cselle @gabor]

@theNiazAhmed Curious what you think it will be

[Gabor Cselle @gabor]

Bay Area dads in 2016: Asking if you watch Silicon Valley
Bay Area dads in 2021: Asking if you’re moving to Austin
Bay Area dads in 2026: Asking if your coding agents are running right now